7 papers
On the Effectiveness of Fact Checking Information from Politically Congruent and Incongruent Large Language Models
Jiangen He, Benjamin D Horne, Dorit Nevo
Social media companies have shifted away from human fact-checkers and instead have embedded conversational Large Language Models (LLM) on their platforms. LLM chatbots differ from…
TextBFGS: A Case-Based Reasoning Approach to Code Optimization via Error-Operator Retrieval
Zizheng Zhang, Yuyang Liao, Chen Chen +8
Iterative code generation with Large Language Models (LLMs) can be viewed as an optimization process guided by textual feedback. However, existing LLM self-correction methods predo…
Seeing to Think? How Source Transparency Design Shapes Interactive Information Seeking and Evaluation in Conversational AI
Jiangen He, Jiqun Liu
Conversational AI systems increasingly function as primary interfaces for information seeking, yet how they present sources to support information evaluation remains under-explored…
Not All Transparency Is Equal: Source Presentation Effects on Attention, Interaction, and Persuasion in Conversational Search
Jiangen He, Jiqun Liu
Conversational search systems increasingly provide source citations, yet how citation or source presentation formats influence user engagement remains unclear. We conducted a crowd…
Who Gets Cited? Gender- and Majority-Bias in LLM-Driven Reference Selection
Jiangen He
Large language models (LLMs) are rapidly being adopted as research assistants, particularly for literature review and reference recommendation, yet little is known about whether th…
Investigating the Impact of LLM Personality on Cognitive Bias Manifestation in Automated Decision-Making Tasks
Jiangen He, Jiqun Liu
Large Language Models (LLMs) are increasingly used in decision-making, yet their susceptibility to cognitive biases remains a pressing challenge. This study explores how personalit…